Evidence from Judiciary Decision Events on Controlling Shareholders in Large Business Groups

Estimating the Value of Absolute Power: Evidence from Judiciary Decision Events on Controlling Shareholders in Large Business Groups

Changmin Lee Hanyang University Business School 222 Wangsimni-ro, Seongdong-gu Seoul, Korea, 133-791 [email protected]

Hansoo Choi Korea Institute of Public Finance 1924 Hannuri-daero Sejong, Korea, 339-007 [email protected]

Estimating the Value of Absolute Power: Evidence from Judiciary Decision Events on Controlling Shareholders in Large Business Groups

Abstract

This paper estimates the impact of judicial decisions, mainly the prosecution and court sentencing of controlling shareholders’ corporate crime, embezzlement, and breach of fiduciary duty, on the market value of a firm. The indictment or imprisonment of controlling shareholders in Korean large business groups, chaebols, provides an experimental setting for analyzing the absence of the real boss.

Our main findings are as follows. First, judicial decisions relating to controlling shareholders generally do not have a significant group-wide effect on the value of a firm. Second, the portion of firms that receive a positive impact and a negative impact from having a controlling shareholder held in custody is almost equivalent (46% versus 54%, respectively). In situations where there is a court appeal, the portion of firms that receive a positive impact decreases to 38%, while the portion of firms that receive a negative impact increases to 62%. Third, the effect of court decisions on affiliated firms within the same business group is asymmetric. For instance, such decisions have a positive effect on affiliates where a controlling shareholder holds a large proportion of the shares; however, they have a negative impact on affiliates thought to be more likely to grow at faster rates in the future. For this reason, sentencing of the controlling shareholder itself induces value transference between the different affiliated firms in a given company group.

Keywords: Family Firm, Controlling Shareholder, Corporate Crime, Judicial System, Event Study JEL classification: G30

Introduction

The controlling shareholder is one popular research topic in the field of finance, especially in governance. Many studies provide theoretical discussions on the benefit and cost of controlling shareholders (Shleifer and Vishny, 1986; Admati, Pfleiderer, and Zechner, 1994; Huddart, 1993; Noe, 1997; Maug, 1998). La Porta et al. (1999) provide empirical evidence that the existence of a controlling shareholder in firm ownership structure is a global phenomenon that includes developed countries. Anderson and Reeb (2003) argue that it is hard to conclude that family ownership of firms is less efficient than non-family owned firms.

The literature is divided into the presence of controlling shareholders with direct involvement in management (Faccio and Lang, 2002; Gadhoum, Lang, and Young, 2005, Villalonga and Amit, 2006b); deviations in controlling shareholders’ cash flow and voting rights (Claessens, Djankov, and Lang, 2000 for East Asia; Joh, 2003 for Korea, Bennedsen, Morten, and Nielsen, 2005 for Western Europe, Villalonga and Amit, 2006b for the United States; Barontini and Caprio, 2006 for Continental Europe); and the impact of management succession on firm performance (Francisco Perez-Gonzalez, 2006; Villalonga and Amit, 2006b).

Korean conglomerates, chaebols, have provided meaningful conclusions in this field because the controlling shareholder (i.e., so-called owner) has an important position in addition to being a large shareholder. Owners are often directly involved in company management. Through complicated governance (e.g., pyramids), owners also exercise control over all affiliated firms within the group. In addition, most reigns are inherited.

We analyze the effects of judicial decisions regarding criminal acts, embezzlement, and breach of fiduciary duty on the market value of a firm. It can be easily anticipated that the prosecuting or sentencing of controlling shareholders has a negative effect on the value of a firm. The temporary absence of the owner due to the outcome of a court decision (e.g., directly by indictment or imprisonment, or indirectly by involvement in a criminal action or stepping down from the CEO position) can have a negative impact on management. Also, prosecuting or sentencing controlling shareholders can seriously damage a firm’s reputation.

The imprisonment or taking into custody of a controlling shareholder provides an experimental setting for analyzing the absence of a company’s boss. Police custody is the first stage of law enforcement, and can cause the first effects on market values. Imprisonment after a court’s final decision is the final stage of law enforcement, and provides a situation where there is no more uncertainty about affecting the market’s expectations.

The recent health issues of Lee Kun-Hee, Samsung’s chairman and CEO, provided important motivation for our paper. During this period, Samsung’s stock prices moved asymmetrically. Some affiliated firms increased and others decreased during the shareholder’s health issues. There seems to be no reason why the hospitalization of a controlling shareholder would have a positive effect on the firm’s fundamentals.

Therefore, this market change can be interpreted as investors expecting value transfer (i.e., tunneling) between Samsung’s affiliated firms. In other words, the absence of the controlling shareholder might induce the transfer of affiliated firms’ resources and values through various means. In the Samsung case, investors anticipated tunneling to the future holding company where Lee Kun-Hee and Lee Jae Young, son of Lee Kyn-Hee, hold large portions of shares.

Our paper is similar to Bennedsen, Pérez-González, and Wolfenzon (2011), which provided evidence for the effect of CEOs on firm performance resulting from the number of days a CEO was hospitalized. They concluded that CEOs meaningfully affected firm performance. In this paper, we focused on controlling shareholders who have real authority over all affiliated firms within the same business group. We analyzed the variation of value effects among all affiliated firms.

Moreover, we contributed to the literature as follows. Our paper is an event study about the value of controlling shareholders as part of the top management team. The literature related to our paper was divided into three categories. The first was the effect of controlling shareholders on the policy and performance of a firm (Baek, Kang and Park; 2004, Bertrand et al; 2008; Anderson, Duru, Reeb; 2009). We estimated the effect of a controlling shareholder’s temporary absence on the market value of a family firm.

The second category included event studies about the value of a firm when an unexpected turn-over or sudden death happened to the CEO (Furtado, 1987; Weisbach, 1988; Bonnier and Bruner, 1989; Furtado and Karan, 1990; Kang and Shivdasani, 1995; Dedman and Lin, 2002; Salas, 2010). We provided empirical evidence for what happened to all affiliated firms within the same business group when the controlling shareholder was absent.

Lastly, many studies showed that tunneling occurred by the controlling shareholder (Shin and Park, 1999; Bae, Kang and Kim, 2002; Campbell and Keys, 2003; Joh, 2003; Baek, Jang and Lee, 2006; Bae, Cheon, and Kang, 2008). Among the above studies, our paper is methodologically similar to Bae, Cheon and Kang (2008). They showed how affiliated firms’ stock prices changed when one affiliated firm within the conglomerate announced an operating profit increase, a positive event. We suggest the possibility that the absence of the controlling shareholder could cause a similar phenomenon due to the expectation for corporate governance restructuring or a succession of control to the next generation.

Our main findings are as follows. First, judicial decisions related to controlling shareholders generally do not have a significant group-wide effect on firm value. Second, the portion of firms that received a positive impact (46%) and a negative impact (54%) from having a controlling shareholder held in custody was almost equivalent. In situations where there was a court appeal, the portion of firms that received a positive impact decreased to 38%, while the portion of firms that received a negative impact increased to 62%. Third, the effect of a court decision on affiliated firms within the same business group was asymmetric. For instance, this had a positive effect on the affiliate at which a controlling shareholder held large portions of shares. However, it had a negative impact on the affiliate most likely to grow fast in the future. That is, sentencing of the controlling shareholder itself induced value transference between affiliated firms.

Sample

Our corporate crime samples covered events violating Korea’s Article 356 of Criminal Law regarding embezzlement and breach of fiduciary duty. We excluded samples regarding collateral frauds, and included banking and accounting fraud.

Within a conglomerate, tunneling can occur by transferring resources from one firm to another underperforming firm. Another method is transferring resources to other firms where it is easier to use the resources privately. A third way is transferring resources to commit finance accounting fraud, which is generally conducted to support troubled firms within the conglomerate.

Our study sample was composed of 18 business conglomerates, chaebols, which committed white-collar crime in Korea from 2000 to 2014. All of the conglomerates were prosecuted and received a verdict in district and high courts. Because the judicial authorities did not archive all the documents pertaining to the criminal cases, collecting the data was arduous work. We collected the data through three channels as follows.

NGO and press reporting Our study was based on a series of reports presented by People’s Solidarity for Participatory Democracy and Solidarity for Economic Reform, which is a civil action group in Korea. We additionally used news and press reports because the above series of reports did not contain a large enough sample, even though it contained detailed information about some crucial and conspicuous corporate crimes. The samples were extracted from news articles from 2000 to 2014 using the key words “embezzlement”, “breach of fiduciary duty”, “court decision”, and “verdict”.

This approach was efficient for searching through considerable information. However, it had the drawback that defendant numbers were not determined exactly because most of the corporate crimes had more than one defendant. Also, because news articles are not always precise, there was the possibility that errors were committed in the reporting process. Therefore, it was necessary to collect more objective and accurate data, such as the courts’ written judgments.

The judiciary written judgment The written judgment is the official and final court sentence. With this information, we concentrated mainly on determining the position of the suspect. We tried to clearly understand whether the suspect was a controlling shareholder or CEO, and whether the suspect was related to the individual firm or if he/she was in a position to exercise power over the whole conglomerate.

Methodology and Analysis

To calculate abnormal return for an event study, we adopted two popular models: the Fama and French (1993) three-factor model and the Carhart (1997) four-factor model.

contains main variable definitions. The 3 Factor Business Group Cumulative Average Abnormal Return (3 Factor Model CAAR) was the sum of averaged abnormal return measured during the event window with the 3 Factor Model. An averaged abnormal return was the average of all individual firms’ abnormal return within the same business group (chaebol).

The 4 Factor Business Group Cumulative Average Abnormal Return (4 Factor Model CAAR) was the sum of averaged abnormal return during the event window measured with the 4 Factor Model. An averaged abnormal return was the average of all individual firms’ abnormal return within the same business group (chaebol).

The 3 Factor Individual Cumulative Abnormal Return (3 Factor Model CAR) was the sum of each individual firm’s abnormal return during the event window measured with the 3 Factor Model. The 4 Factor Individual Cumulative Abnormal Return (4 Factor Model CAR) was the sum of each individual firm’s abnormal return during the event window measured with the 4 Factor Model.

Our sample included prosecutor and court decisions on corporate crimes. We included prosecutor decisions for 10 cases (i.e., 10 associated business groups), representing a total of 80 affiliated firms. Court decisions were for 18 cases (i.e., 18 associated conglomerates), representing 176 affiliated firms.

and

shows the abnormal return for prosecutor indictment cases. We set up a seven day event window. In Panel A, the 3 Factor Model CAAR was -1.33% and the 4 Factor Model CAAR was -0.84%; however, this was not statistically significant. The 3 Factor Model CAR was marginally significant at -2.11%, while the 4 Factor Model CAR was -1.67%. In general, there was no strong evidence that the prosecutor’s decision had a positive or negative effect on firm value.

Panel B shows the abnormal return for a sub-sample of cases involving pre-trial detention. The 3 Factor Model CAAR was -3.31% and the 4 Factor Model CAAR was -3.25%; however, this was not statistically significant. The 3 Factor Model CAR was -4.51% and the 4 Factor Model CAR was -4.32%, which were both statistically significant. This occurred because the portion of affiliated firms with negative effects, regardless of the business group, was larger than 50%. (See in Panel C)

Panel C implies that the effect of prosecution on individual affiliated firms was asymmetric. Positive effects were observed for 23 firms (46%) and negative effects for 27 firms (54%).

shows the business groups’ AAR (Average Abnormal Return) and CAAR, and the affiliated firms’ AR (Abnormal Return), CAR before and CAR after the prosecution decision for the Samsung Everland case on April 17, 2008 from the 3 Factor Model. For the group perspective, this appeared to have a positive effect; however, it was divided into a positive and a negative effect for each affiliated firm.

shows the business groups’ AAR and CAAR, and the affiliated firms’ AR, CAR before and CAR after the prosecution decision for the CJ case on July 18, 2013 from the 3 Factor Model. This showed a negative result for the group perspective, while it had an asymmetric result for individual firms.

and

shows the abnormal return for court decision cases. In Panel A, the 3 Factor Model CAAR was -0.56% and the 4 Factor Model CAAR was 0.01%, which was not statistically significant. The 3 Factor Model CAR was -0.87% and the 4 Factor Model CAR was -0.92%, which was also not statistically significant.

Panel B and C show that the number of firms experiencing a positive effect on firm value even though a controlling shareholder was imprisoned was 47 (3 factor CAR) and 48 (4 factor CAR) out of 98 firms.

In Panel D, we show that 37% to 39.1% of affiliated firms had a positive CAR even though the controlling shareholder was imprisoned by the final court.

shows the business groups’ AAR and CAAR, and the affiliated firms’ AR, CAR before and CAR after the decision for probation in the case of Samsung Everland on July 16, 2008 from the 3 Factor Model. This had a positive effect for the group perspective; however, it was divided into a positive and a negative effect for each affiliated firm.

shows the business groups’ AAR and CAAR, and the affiliated firms’ AR, CAR before and CAR after the probation decision at the first trial of the Hansol case on May 27, 2005 from the 4 Factor Model. This showed a positive result for the group perspective, while it had an asymmetric result for individual firms. This result is similar to the SK case in

, the high court imprisonment sentence on February 27, 2014. This clearly showed a positive impact for the group, and an asymmetric impact for individual firms.

, we provide evidence that the difference in CAAR between pretrial detention and no pretrial detention is not statistically significant. In

, the 3 factor CAAR and the 4 factor CAAR in pretrial detention cases were -3.32% and -3.25%, respectively. The 3 factor CAAR and the 4 factor CAAR in cases of no pretrial detention were 2.78% and 3.02%. There was no significant difference between the two cases.

provides evidence that the difference in CAAR between probation and imprisonment at the court sentencing was not statistically significant either. In

, the 3 factor CAAR and the 4 factor CAAR in cases of probation at the second trial were - 3.33% and -3.54%, respectively (Panel C). The 3 factor CAAR and the 4 factor CAAR in cases of imprisonment were -3.08% and -3.62%, respectively. There was no significant difference between the two cases.

shows the daily AAR for each business group during the event window for indictment and sentencing.

is the result of the regression analysis. We estimated the effects of prosecutor and court decision on each affiliated firm. The dependent variable was CAR. In

and

, the first regression showed that pretrial detention did not have any significant effect on firm value. The third regression suggested that imprisonment had positive or no effect on firm value.

and

, the first regression showed that there was a negative 10

effect on firms when a controlling shareholder held large portions of shares during the pretrial stage. The second and third regressions showed that there was a positive effect on firms when a controlling shareholder held large portions of shares, and negative effect on growing firms (i.e., higher MTB firm) during trial. The third regression showed that the coefficient of firm size and variation of stock return were positive, but MTB was negative. This implied that large-sized affiliated firms and affiliated firms with uncertain circumstances received positive effects, while growing firms received negative effects.

Conclusion

We analyze judicial decision effects on firm values when a conglomerate’s controlling shareholder committed crimes. We provide the following evidences. First, judicial decisions relating to controlling shareholders generally do not have a significant group-wide effect on the value of a firm. Second, the portion of firms that receive a positive impact and a negative impact from having a controlling shareholder held in custody is almost equivalent (46% versus 54%, respectively). In situations where there is a court appeal, the portion of firms that receive a positive impact decreases to 38%, while the portion of firms that receive a negative impact increases to 62%. Third, the effect of court decisions on affiliated firms within the same business group is asymmetric. For instance, such decisions have a positive effect on affiliates where a controlling shareholder holds a large proportion of the shares; however, they have a negative impact on affiliates thought to be more likely to grow at faster rates in the future.

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Description: Variables

Variable Description 3 Factor Business Group Cumulative Average Sum of business group averaged abnormal return during the Abnormal Return (3 Factor Model CAAR) event window measured by 3 Factor Model

Sum of business group averaged abnormal return during the 4 Factor Business Group Cumulative Average event window measured by 4 Factor Model Abnormal Return (4 Factor Model CAAR)

Sum of each individual firm’s abnormal return during the event 3 Factor Individual Cumulative Abnormal window measured by 3 Factor Model Return (3 Factor Model CAR)

Sum of each individual firm’s abnormal return during the event 4 Factor Individual Cumulative Abnormal window measured by 4 Factor Model Return (4 Factor Model CAR) 1 if the controlling shareholder (defendant) is indicted in Pretrial detention custody; otherwise, 0

1 if the controlling shareholder (defendant) goes to the prison; Imprisonment otherwise, 0 in the case of probation

1 if the decision is made at the second trial or later; otherwise, Instance 0 in the case of the first trial

Summary statistics

Variable: court decisions Observations Number of prosecutor decisions (Number of business 10 groups, chaebols) Number of individual firm related corporate crimes 89 Number of court decisions (Number of business groups, 18 chaebols) Number of individual firm related corporate crimes 176 Variable: financial characteristics Mean (Observations) Total assets (Million Won) 6,279,986 Financial leverage 3.05 (164) ROA (Return on Assets) 2.12% (176) ROE (Return on Equity) 4.54% (175) MTB (Market-to-Book Ratio) 1.72 (176) Stock price volatility (Average of 52 weeks) 2.64% (176) Variable: corporate governance Mean (Observations) Portion of controlling shareholder (defendant) ownership 2.51% (176) Portion of family ownership 2.44% (176) Portion of subsidiaries ownership 27.54% (176) Size of board of directors 7.68 (176) Portion of outside director 52.29% (176)

CAAR(-7, +7) and CAR(-7, +7): Prosecutor Indictment event

Panel A: All events

Business group Individual firm 3 Factor Model 4 Factor Model 3 Factor Model 4 Factor Model Model CAAR CAAR CAR CAR Observations 10 10 89 89 Mean -0.0133 -0.0084 -0.0211* -0.0167 Standard 0.0716 0.0713 0.1366 0.1369 deviation Min -0.2031 -0.2028 -0.7671 -0.7667 Max 0.0739 0.0753 0.1902 0.1910

Panel B: Pre-trial detention

Business group Individual firm 3 Factor Model 4 Factor Model 3 Factor Model 4 Factor Model Model CAAR CAAR CAR CAR Observations 5 5 50 50 Mean -0.0332 -0.0325 -0.0451** -0.0432** Standard 0.0956 0.0955 0.1671 0.1680 deviation Min -0.2031 -0.2028 -0.7671 -0.7667 Max 0.0239 0.0235 0.1757 0.1910

Panel C: CAR by Pre-trial detention

Observations CAR>0 CAR<0 3 Factor 50 23 (46%) 27 (54%) 4 Factor 50 23 (46%) 27 (54%)

CAAR(-7, +7) and CAR(-7, +7): Court decision event

Panel A: All events

Business group Individual firm 3 Factor 4 Factor Model 3 Factor Model 4 Factor Model Model Model CAAR CAAR CAR CAR Observations 18 18 176 176 Mean -0.0056 0.0001 -0.0087 -0.0092 Standard 0.0744 0.0853 0.1148 0.1423 deviation Min -0.1662 -0.1899 -0.4488 -0.4493 Max 0.1478 0.1543 0.4005 0.4829

Panel B: CAR by sentencing outcome and instance (3 Factor Model)

Observations CAR>0 CAR<0 Imprisonment 98 47 51 Probation 78 30 48 First trial 90 46 44 Second trial 86 31 55

Panel C: CAR by sentencing outcome and instance (4 Factor Model)

Observations CAR>0 CAR<0 Imprisonment 98 48 50 Probation 78 29 49 First trial 90 45 45 Second trial 86 32 54

Panel D: CAR by Second Trial and Imprisonment (3 and 4 Factor Model)

Observations CAR>0 CAR<0 3 Factor 46 18 (39.1%) 28 (61.9%) 4 Factor 46 17 (37%) 29 (63%)

CAAR(-7, +7) of Business group: Prosecutor Indictment event

***, **, * represent statistical significance at 1%, 5%, 10% level.

Panel A: Total sample No Total Pretrial detention Difference Pretrial detention Observations 9 4 5 3 Factor Model -0.0061 0.0277 -0.0332 0.0609 4 Factor Model -0.0046 0.0302 -0.0325 0.0627

CAR(-7, +7) of Individual firm: Prosecutor Indictment event

***, **, * represent statistical significance at 1%, 5%, 10% level.

Panel A: Total sample No Total Pretrial detention Difference Pretrial detention Observations 80 30 50 3 Factor Model -0.0204 0.0208 -0.0451 0.0659** 4 Factor Model -0.0184 0.0231 -0.0432 0.0663**

CAAR(-7, +7) of Business group: Court decision event

***, **, * represent statistical significance at 1%, 5%, 10% level.

Panel A: Total sample Total Probation Imprisonment Difference Observations 18 9 9 3 Factor Model -0.0056 -0.0128 0.0015 0.0144 4 Factor Model 0.0001 -0.0174 0.0178 0.0352

Panel B: Total sample Total First trial Second trial Difference Observations 18 10 8 3 Factor Model -0.0056 0.0154 -0.0320 0.0475 4 Factor Model 0.0001 0.0289 -0.0358 0.0648

Panel C: Second trial sub-sample Total Probation Imprisonment Difference Observations 8 4 4 3 Factor Model -0.0320 -0.0333 -0.0308 0.0024 4 Factor Model -0.0358 -0.0354 -0.0362 0.0008

CAR(-7, +7) of Individual firm: Court decision event

***, **, * represent statistical significance at 1%, 5%, 10% level.

Panel A: Total sample Total Probation Imprisonment Difference Observations 176 78 98 3 Factor Model -0.0087 -0.0207 0.0008 0.0216 4 Factor Model -0.0092 -0.0425 ** 0.0172 0.0597 ***

Panel B: Total sample Total First trial Second trial Difference Observations 176 90 86 3 Factor Model -0.0087 0.0144 -0.0329 *** 0.0473 *** 4 Factor Model -0.0092 0.0202 -0.0400 ** 0.0602 ***

Panel C: Second trial sub-sample Total Probation Imprisonment Difference Observations 86 40 46 3 Factor Model -0.0329 -0.0571 ** -0.0118 0.0452 * 4 Factor Model -0.0400 -0.0681 ** -0.0156 0.0525 *

Market reaction of business group level based on indictment date (3 Factor Model)

indictment AAR CAAR CAAR CAAR -6 -5 -4 -3 -2 -1 date 1 2 3 4 5 6 7 (-7) (-7,7) (-7,-1) (1,7) 0 SK -1.15 1.37 -2.63 -4.44 -1.30 -3.12 -2.34 -6.61 -4.36 -5.82 -0.62 -3.13 6.67 0.83 6.34 -20.31 -13.61 -0.09 (2003.03) *** *** *** * *** ** *** * ** ** *** *** ** *** Dongkuk 1.12 0.22 2.33 0.51 1.79 0.56 -0.95 -1.05 0.45 1.22 -1.15 -1.32 -2.68 0.13 3.75 4.94 5.57 0.41 Steel (2004.07) * * ** ** Dongbu 0.10 0.98 -1.62 -1.21 -0.83 0.16 -0.02 0.91 -2.85 0.58 1.76 0.93 -1.16 0.24 -1.02 -3.06 -2.45 -1.64 (2004.05) * DOOSAN -1.34 1.54 -1.60 -1.06 -1.22 1.64 2.02 0.54 -1.11 4.60 3.80 -0.95 -1.63 0.57 1.59 7.39 -0.02 6.87 (2005.11) ** * * ** * Hansol 1.25 1.82 0.02 -0.49 0.45 0.82 0.21 0.22 -2.28 1.16 -0.35 -0.52 -0.28 -0.32 -0.61 1.10 4.08 -3.20 (2004.09) * * KIA 0.19 0.18 -1.52 -0.02 -0.33 -0.06 0.12 -1.09 -0.61 -0.29 3.69 -0.59 -0.65 0.30 -0.90 -1.58 -1.45 0.95 (2006.05) * * Samsung 0.49 0.49 0.54 -0.30 0.51 -0.17 0.12 0.90 1.47 -0.55 -1.36 -0.31 0.42 0.18 -0.62 1.81 1.67 -0.77 (2008.04) ** * Hanwha 0.28 0.05 -0.29 0.82 0.69 -0.51 0.41 0.75 -1.35 -1.35 -1.35 -1.35 -0.11 0.28 -0.07 -3.09 1.46 -5.30 (2011.01) SK 0.60 -1.49 -0.45 -0.45 -1.31 1.20 1.48 0.94 -0.61 0.95 0.49 -0.28 0.94 -0.31 0.59 2.29 -0.42 1.77 (2012.01) ** * * ** CJ 0.19 -0.72 1.48 -0.04 -0.97 -0.09 1.31 0.71 -0.99 -0.53 -0.86 -0.41 -0.30 0.33 -1.88 -2.76 1.16 -4.63 (2013.07) * * * ** ** ** ** Average of 0.17 0.44 -0.37 -0.67 -0.25 0.04 0.23 -0.38 -1.22 0.00 0.41 -0.79 0.12 0.22 0.72 -1.33 -0.40 -0.55 Business ** ** * group Average of 0.18 0.26 -0.45 -0.86 -0.44 -0.08 0.26 -0.44 -1.12 -0.43 0.14 -0.79 0.78 0.19 0.68 -2.11 -1.13 -0.55 Individual * *** * ** ** ** *

Market reaction of business group level based on sentencing date (3 Factor Model)

sentencing AAR CAAR CAAR CAAR -6 -5 -4 -3 -2 -1 date 1 2 3 4 5 6 7 (-7) (-7,7) (-7,-1) (1,7) 0

SK -2.10 2.77 2.63 4.87 -3.75 -0.43 -1.45 0.36 -0.01 0.4 1.26 0.23 -0.11 -1.63 -1.19 1.85 1.76 -4.78 (2003.06) * ** * *** ** - Dongkuk -3.51 -8.21 Steel -3.22 -0.37 0.91 -1.25 -3.38 0.90 -1.8 1.42 -0.96 -2.00 2.17 1.86 -0.28 -0.80 10.31 -3.52 ** ** (2004.12) ** Dongbu -1.66 3.04 -1.43 3.95 2.33 5.58 14.79 5.74 0.34 -0.82 1.53 1.53 0.00 -1.24 -0.39 -0.49 2.52 7.51 (2005.02) ** * * * ** ** * *

Hansol 4.40 0.01 0.99 0.76 -0.96 -0.47 -0.86 -0.3 1.72 1.32 -0.57 0.30 0.81 1.47 -1.49 1.67 -0.83 3.51 (2005.05) *

SK 2.24 -0.91 -1.22 2.09 0.71 1.39 -0.19 0.40 -0.98 -0.46 -0.80 0.70 -0.06 0.55 -1.03 2.41 3.1 0.11 (2005.06) * * * *

Dongbu -3.47 -2.87 3.24 -0.82 1.85 0.18 -0.28 3.30 0.21 3.13 -0.5 0.86 -1.46 -0.76 -0.92 1.71 0.98 -2.4 (2005.09) ** * ***

DOOSAN -1.35 -1.64 -4.06 1.77 -1.86 -7.99 -6.95 -0.76 -2.68 1.59 1.96 -1.58 -0.62 -0.18 0.47 0.21 0.74 0.54 (2006.02) * * ** * *** ** **

DOOSAN 0.23 -1.49 0.41 0.34 -1.49 0.73 0.79 -0.84 0.35 1.66 -0.08 -0.21 -1.71 0.38 0.14 -0.81 -0.49 0.52 (2006.07) Hyundai Motor 1.03 1.41 1.41 7.61 5.74 0.02 0.48 0.10 -0.43 0.02 0.48 0.18 0.06 0.86 0.05 0.53 1.40 1.69 Group ** ** * ** ** (2007.02) Samsung -1.57 -3.89 -2.1 2.01 2.19 -2.81 0.93 1.12 3.88 1.82 -1.07 -6.49 6.42 -0.31 -0.14 -0.35 1.16 0.86 (2008.07) * *** ** * *** *** * ** *** *** * *** ***

sentencing AAR CAAR CAAR CAAR -6 -5 -4 -3 -2 -1 date 1 2 3 4 5 6 7 (-7) (-7,7) (-7,-1) (1,7) 0 - Samsung 1.54 -1.13 -1.80 -6.10 -6.70 2.98 3.77 -0.92 -9.34 -6.51 -0.34 0.13 1.20 -0.52 1.52 -0.91 16.63 -3.42 (2008.10) * ** * *** *** ** *** * *** ** *** Hanwha -0.56 7.74 3.57 0.07 0.05 1.05 1.62 1.39 -0.05 -0.35 1.68 0.74 -0.19 0.84 1.58 -0.34 0.22 4.52 (2012.08) ** * *

SK -0.89 -0.64 -1.35 -0.78 -4.39 -2.26 -0.19 0.25 -0.78 0.01 -0.01 -0.64 -0.68 0.21 0.72 0.55 -0.15 -1.5 (2013.01) *** ** ** ** *** ***

Hanwha -2.28 -1.20 1.85 -1.89 -1.98 -9.29 -3.14 -4.25 -0.41 -0.02 -0.59 -0.49 -1.89 -0.76 0.59 0.01 -0.86 0.63 (2013.04) *** * * * * ** ** *

SK -1.25 0.06 0.22 0.02 0.64 -0.33 0.33 0.16 -0.08 0.07 0.57 0.19 -0.13 -0.2 -0.13 0.13 1.09 -0.88 (2013.09) **

Hanwha -1.91 -1.11 -1.17 1.06 -1.23 -1.93 -4.84 -2.07 0.96 -0.83 -0.11 0.91 0.49 0.59 -0.72 -0.2 0.37 -1.61 (2014.02) * * *** * ** *** *** *

CJ -2.03 1.75 -1.63 1.77 0.23 0.16 -0.27 0.11 -0.33 0.6 0.23 0.08 0.56 0.37 -0.67 0.93 -0.38 0.72 (2014.02) *** ** *** ***

SK -1.2 0.7 -0.29 0.36 0.44 0.03 0.3 0.11 0.29 -0.17 0.74 0.05 -0.06 0.44 -0.09 1.64 0.33 1.19 (2014.02) ** * Average of Business -0.42 -0.44 -0.27 -0.04 -0.13 0.3 -0.03 0.02 0.20 0.18 0.38 -0.41 -0.54 0.19 0.45 -0.57 -1.03 0.44 group Average of -0.45 -0.52 0.48 -0.77 -0.38 -1.06 -0.30 0.19 0.07 -0.05 0.00 -0.20 0.27 0.34 0.31 0.13 -0.87 0.38 Individual ** ** ** *** * * ***, **, * represent statistical significance in 1%, 5%, 10% significant level.

Market reaction of business group level based on indictment date (4 factor Model)

sentencing AAR CAAR CAAR CAAR -6 -5 -4 -3 -2 -1 date 1 2 3 4 5 6 7 (-7) (-7,7) (-7,-1) (1,7) 0 SK -1.05 1.41 -2.51 -4.51 -1.21 -3.04 -2.15 -6.61 -4.52 -5.85 -0.33 -2.73 6.32 0.66 5.85 -20.28 -24.20 -0.60 (2003.03) *** *** *** * *** * *** * ** ** *** *** ** *** Dongkuk 1.11 0.19 2.35 0.51 1.77 0.57 -0.95 -1.05 0.47 1.18 -1.11 -1.33 -2.70 0.11 3.77 4.88 4.98 0.38 Steel (2004.07) ** ** ** ** Dongbu 0.33 0.81 -1.29 -1.14 -0.80 0.52 -0.13 0.67 -2.93 0.88 1.88 1.09 -1.26 0.28 -1.14 -2.24 -3.96 -1.21 (2004.05) * DOOSAN -1.34 1.51 -1.54 -1.05 -1.21 1.64 2.01 0.48 -1.08 4.65 3.81 -0.93 -1.68 0.59 1.64 7.53 -0.56 7.01 (2005.11) * * * ** * Hansol 0.65 1.75 0.82 -0.48 -0.52 0.33 0.36 0.00 -2.24 1.22 -0.14 -1.37 -0.62 0.22 0.47 0.45 0.67 -2.46 (2004.09) * * KIA 0.24 0.26 -1.34 0.46 -0.30 -0.17 0.48 -0.57 -0.06 0.13 3.63 -0.56 -1.03 0.26 -1.09 0.33 -1.01 1.28 (2006.05) * * * Samsung 0.49 0.49 0.57 -0.25 0.54 -0.18 0.12 0.92 1.44 -0.56 -1.36 -0.36 0.43 0.22 -0.61 1.90 4.13 -0.80 (2008.04) ** * ** Hanwha 0.26 0.00 -0.36 0.78 0.59 -0.66 0.44 0.72 -1.30 -1.30 -1.30 -1.30 -0.06 0.38 -0.02 -3.12 0.47 -4.89 (2011.01) SK 0.59 -1.49 -0.46 -0.46 -1.30 1.22 1.47 0.93 -0.61 0.97 0.50 -0.26 0.97 -0.30 0.59 2.35 -0.12 1.86 (2012.01) ** * ** CJ 0.57 -0.69 1.30 -0.03 -0.03 0.00 0.79 0.71 -0.59 -0.17 -0.77 0.27 -0.33 0.60 -1.83 -0.20 2.03 -2.82 (2013.07) ** * Average of Business 0.19 0.42 -0.25 -0.62 -0.25 0.02 0.24 -0.38 -1.14 0.11 0.48 -0.75 0.00 0.30 0.76 -0.84 -1.76 -0.23 group * * *** Average of 0.20 0.25 -0.34 -0.82 -0.41 -0.09 0.26 -0.44 -1.06 -0.33 0.22 -0.73 0.67 0.25 0.70 -1.67 -0.95 -0.28 Individual *** * ** ** * **

Market reaction of business group level based on indictment date (4 factor Model, continued)

sentencing AAR CAAR CAAR CAAR -6 -5 -4 -3 -2 -1 date 1 2 3 4 5 6 7 (-7) (-7,7) (-7,-1) (1,7) 0 SK 4.54 8.24 3.64 3.81 -3.92 -1.39 15.43 6.4 -0.16 -0.06 -1.29 0.24 0.94 2.18 0.72 0.01 -2.08 0.79 (2003.06) *** *** ** * ** * ** * Dongkuk -3.99 -2.18 -0.48 -5.85 Steel -1.48 0.83 -0.1 -1.99 1.7 -0.83 0.48 -1.35 0.03 3.91 0.92 -1.1 -5.62 -0.25 * ** * ** (2004.12) Dongbu -1.32 -2.4 4.87 2.50 0.77 2.37 0.48 -0.38 0.41 3.4 -1.31 -0.86 -0.85 1.09 3.67 12.43 4.38 5.55 (2005.02) * ** ** *

Hansol -1.77 3.07 2.93 -3.01 0.26 -0.85 0.52 -0.38 -0.24 -0.55 -0.8 0.05 0.44 0.48 -0.92 -0.11 2.11 2.06 (2005.05) ** ** * *

SK -1.7 -1.05 -1.92 2.58 1.23 0.17 -1.26 0.24 -1.12 1.4 1.43 0.55 0.01 1.00 -0.97 0.6 2.09 0.2 (2005.06) ** * ** **

Dongbu -2.03 3.31 -0.89 1.37 -0.01 -0.43 1.84 0.53 2.18 -0.45 -1.5 0.91 -2.45 0.61 -0.75 2.25 0.38 -0.32 (2005.09) * ***

DOOSAN 1.65 -1.61 -0.48 -0.43 -2.04 -1.00 1.56 0.90 -1.42 -1.29 0.74 -0.90 0.03 -0.45 1.59 -3.13 -3.08 1.37 (2006.02) *

DOOSAN -1.71 3.32 0.12 -0.99 0.26 -0.22 0.01 -1.14 0.57 1.72 -0.26 0.82 -1.35 0.67 0.18 1.98 0.78 2.34 (2006.07) ** ** Hyundai Motor 2.93 2.08 2.44 9.37 4.78 4.89 0.93 -0.23 -0.21 0.28 0.97 0.1 -0.3 -0.71 -0.09 0.02 0.9 0.24 Group *** *** ** *** * * (2007.02) - Samsung -1.48 -5.07 -3.3 -5.09 -0.77 5.98 2.31 -2.17 -7.37 5.15 1.66 0.33 0.11 0.32 -0.01 0.22 -0.4 12.85 (2008.07) * *** *** *** * *** *** *** *** *** *** 24

Market reaction of business group level based on indictment date (4 factor Model, continued)

sentencing AAR CAAR CAAR CAAR -6 -5 -4 -3 -2 -1 date 1 2 3 4 5 6 7 (-7) (-7,7) (-7,-1) (1,7) 0 - - Samsung -1.02 -1.81 -5.14 -9.90 2.14 -4.75 10.1 -2.11 -9.27 2.93 -1.21 0.98 -0.10 -1.43 1.59 18.99 14.86 0.62 (2008.10) * *** *** *** ** *** *** *** *** *** * *** *** Hanwha 1.87 3.59 0.89 9.98 7.39 -0.61 0.25 0.97 0.42 -0.26 1.88 0.54 -0.48 0.23 0.62 -0.18 0.24 2.85 (2012.08) * * *** * **

SK -0.98 -0.65 -0.57 -1.08 -0.74 -0.82 1.08 -0.69 -0.45 -5.09 -2.39 -0.47 -0.37 0.13 0.52 -0.52 0.52 -1.62 (2013.01) ** ** * ** * ** * ** * *** *** - Hanwha -2.23 -0.49 1.84 -2.82 -2.4 -3.37 -4.48 -0.79 -1.06 -0.05 -0.57 -1.67 -1.25 1.69 -0.91 -0.11 0.18 10.66 (2013.04) *** * ** ** ** ** * ** SK -0.46 -0.70 -0.81 -0.03 -0.04 -0.13 0.38 0.04 0.43 0.04 -0.28 -0.7 0.23 0.08 -0.41 -2.36 0.69 -2.59 (2013.09) * * *

Hanwha -2.49 -1.05 -0.79 1.49 -2.73 -5.23 -3.29 0.64 -0.53 0.31 -0.44 0.29 0.78 -0.39 -0.47 -0.81 0.97 -1.16 (2014.02) * * ** ** *** *** **

CJ -1.7 0.56 -1.03 -1.46 1.41 0.63 0.18 0.39 1.13 0.38 -0.73 -0.06 1.03 -0.07 0.19 0.84 0.27 0.63 (2014.02) *** * ** ** **

SK -0.96 1.03 0.76 0.71 1.49 -0.03 0.43 0.22 0.22 -0.16 0.24 -0.35 0.35 0.28 -0.51 3.74 1.67 2.23 (2014.02) ** ** ** * ** Average of Business -0.24 -0.56 -0.47 -0.23 0.05 0.02 0.33 0.10 -0.28 0.92 0.35 -0.24 -0.15 0.14 0.28 0.02 -1.1 1.01 group Average of -0.73 -0.77 1.04 0.43 -1.81 -0.15 -0.08 0.1 -0.41 0.22 -0.04 -0.31 -0.47 0.01 0.33 -0.1 -0.92 0.93 Individual *** *** *** * ** ***, **, * represent statistical significance in 1%, 5%, 10% significant level. 25

CAR(-7, +7) Regression results (3 Factor Model)

***, **, * represent statistical significance in 1%, 5%, 10% significant level. The numbers in ( ) are t-value. (2) (3) (1) Total sentencing Second trial Total pre-trial sample sample sub-sample

-0.0538 Pre-trial detention (-1.01)

-0.0462*** Instance (-2.69) 0.0156 0.0619** Imprisonment (0.88) (2.36)

-1.50e-12 8.82e-10 1.03e-09* Total assets (-0.58) (1.53) (1.92) 0.00006 0.0011 -0.0052 Leverage (0.00) (0.29) (-1.25) MTB (Market-to-Book -0.0137 -0.0241*** -0.0347*** ratio) (-0.90) (-3.35) (-3.66) -1.4875 1.5305 3.2047* Stock revenue volatility (-0.55) (1.47) (1.88) ROA (Return On 0.0051 0.0006 0.0009 Asset) (1.07) (0.45) (0.48)

Portion of controlling -0.0070** 0.0032** 0.0039 shareholder ( -2.25) (2.13) (1.64) (defendant) ownership Portion of family 0.0073 0.0001 0.0011 ownership (1.29) (0.07) (0.37) Portion of subsidiaries -0.00005 -0.0002 -0.0002 ownership (-0.04) (-0.54) (-0.30) Size of board of 0.0018 -0.0050 -0.0015 directors (0.15) (-1.32) (-0.23) Portion of outside 0.1764 -0.0493 -0.0873 director (1.61) (-0.63) (-0.65)

0.1291 0.0618 -0.0254 Constant (0.63) (1.09) (-0.24) Fixed Effect Yes Yes Yes R-squared 0.5049 0.2399 0.3405 Observations 55 164 81

CAR(-7, +7) Regression results (4 Factor Model)

***, **, * represent statistical significance in 1%, 5%, 10% significant level. The numbers in ( ) are t-value. (1) (2) (3) Total pre-trial Total sentencing Second trial sample sample sub-sample

-0.0544 Pre-trial detention (-1.03)

-0.0436** Instance (-2.20) 0.0671*** 0.0615 Imprisonment (2.84) (1.60)

-1.73e-12 3.15e-10 4.49e-10 Total assets (-0.67) (0.40) (0.71) -0.0008 0.0034 -0.0081* Leverage (-0.05) (0.70) (-1.69) -0.0151 -0.0346*** -0.0373*** MTB (Market-to-Book ratio) (-1.00) (-4.89) (-3.59) -0.6503 3.7421** 4.2598* Stock revenue volatility (-0.24) (2.62) (1.77) 0.0059 0.0005 -0.0023 ROA (Return On Asset) (1.23) (0.782) (-0.88)

Portion of controlling -0.0071** 0.0045** 0.0041 shareholder (defendant) (-2.31) (2.55) (1.46) ownership 0.0069 -0.0011 0.0011 Portion of family ownership (1.24) (-0.51) (0.32) Portion of subsidiaries -0.00008 -0.0002 -0.0006 ownership (-0.07) (-0.33) (-0.78) 0.0005 0.0017 -0.0014 Size of board of directors (0.04) (0.36) (-0.18) 0.1777 -0.1583 0.0295 Portion of outside director (1.64) (-1.58) (0.20)

0.0671 -0.0104 -0.0842 Constant (0.33) (-0.16) (-0.71) Industry Fixed Effect Yes Yes Yes R-squared 0.5042 0.3069 0.3372 Observations 55 164 81

AAR & CAAR from 3 Factor Model: Samsung (Indictment, 2008/04/17)

The first graph shows the business group AAR (Average Abnormal Return) and CAAR (Cumulative Average Abnormal Return), and the others show the affiliated firms AR (Abnormal Return) and CAR (Cumulative Abnormal Return). Black lines represent AAR (AR), and gray lines represent CAAR (CAR).

AAR & CAAR from 3 Factor Model: Samsung first trial (Probation, 2008/07/16)

AAR & CAAR from 3 Factor Model: CJ (Indictment, 2013/07/18)

This figure shows the group average AAR (Average Abnormal Return) and CAAR (Cumulative Average Abnormal Return). The first graph shows the business group AAR and CAAR, and the others show the affiliated firms AR and CAR. Black lines represent AAR (AR), and gray lines represent CAAR (CAR).

AAR & CAAR from 3 Factor Model: CJ First trial (Imprisonment, 2014/02/14)

AAR & CAAR from 4 Factor Model: Hansol (Indictment, 2004/09/04)

This figure shows the group average AAR (Average Abnormal Return) and CAAR (Cumulative Average Abnormal Return). The first graph shows the business group AAR and CAAR, and the others show the affiliated firms AR and and CAR. Black lines represent AAR (AR), and gray lines represent CAAR (CAR).

AAR & CAAR from 4 Factor Model: Hansol First trial (Probation, 2005/05/27)

AAR & CAAR from 4 Factor Model: SK (Indictment, 2012/01/05)

This figure shows the group average AAR (Average Abnormal Return) and CAAR (Cumulative Average Abnormal Return). The first graph shows the business group AAR and CAAR, and the others show the affiliated firms AR and and CAR. Black lines represent AAR (AR), and gray lines represent CAAR (CAR).

AAR & CAAR from 4 Factor Model: SK Second trial (Imprisonment, 2014/02/27)